In machine learning, we generally train a single model to perform a specific task.
By focusing on a single task, we risk ignoring additional information that could help us learn a better representation of the desired task.
Instead, MTL [1]} aims to solve multiple related tasks simultaneously.
Thus, it facilitates the transfer of shared knowledge across relevant tasks [2]}, [3]}.
